中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

19 records (took 0.019 seconds)

    AUGMENTED REALITY PREDICTIONS USING MACHINE LEARNING
    11.
    发明申请
    AUGMENTED REALITY PREDICTIONS USING MACHINE LEARNING 审中-公开

    公开(公告)号：US20190213403A1

    公开(公告)日：2019-07-11

    申请号：US15868531

    申请日：2018-01-11

    Applicant: Adobe Inc.

    Inventor： Kushal Chawla ,  Gaurush Hiranandani ,  Aditya Jain ,  Vaishnav Pawan Madandas ,  Moumita Sinha

    IPC: G06K9/00 ,  G06T19/00

    Abstract: Systems and methods are disclosed herein for determining user behavior in an augmented reality environment. An augmented reality application executing on a computing system receives a video depicting a face of a person. The video includes a video frame. The augmented reality application augments the video frame with an image of an item selected via input from a user device associated with a user. The augmented reality application determines, from the video frame, a score representing an action unit. The action unit represents a muscle on the face of the person depicted by the video frame and the score represents an intensity of the action unit. The augmented reality application calculates, from a predictive model and based on the score, an indicator of intent of the person depicted by the video.

    Predicting joint intent-slot structure
    12.
    发明授权
    Predicting joint intent-slot structure 有权

    公开(公告)号：US11475220B2

    公开(公告)日：2022-10-18

    申请号：US16797164

    申请日：2020-02-21

    Applicant: ADOBE INC.

    Inventor： Somak Aditya ,  Sharmila Nangi Reddy ,  Pranil Joshi ,  Kushal Chawla ,  Bhavy Khatri ,  Abhinav Mishra

    IPC: G06F40/284 ,  G06N3/08 ,  G06F40/117 ,  G06F40/30 ,  G06N3/04

    Abstract: Systems and methods for natural language processing (NLP) are described. The systems may be trained by identifying training data including clean data and noisy data; predicting annotation information using an artificial neural network (ANN); computing a loss value for the annotation information using a weighted loss function that applies a first weight to the clean data and at least one second weight to the noisy data; and updating the ANN based on the loss value. The noisy data may be obtained by identifying a set of unannotated sentences in a target domain, delexicalizing the set of unannotated sentences, finding similar sentences in a source domain, filling at least one arbitrary value in the similar delexicalized sentences, generating annotation information for the similar delexicalized sentences using an annotation model for the source domain, and applying a heuristic mapping to produce annotation information for the sentences in the target domain.

    Generating summary content tuned to a target characteristic using a word generation model
    14.
    发明授权
    Generating summary content tuned to a target characteristic using a word generation model 有权

    公开(公告)号：US11062087B2

    公开(公告)日：2021-07-13

    申请号：US16262655

    申请日：2019-01-30

    Applicant: Adobe Inc.

    Inventor： Balaji Vasan Srinivasan ,  Kushal Chawla ,  Mithlesh Kumar ,  Hrituraj Singh ,  Arijit Pramanik

    IPC: G06F40/284 ,  G06N20/00

    Abstract: Certain embodiments involve tuning summaries of input text to a target characteristic using a word generation model. For example, a method for generating a tuned summary using a word generation model includes generating a learned subspace representation of input text and a target characteristic token associated with the input text by applying an encoder to the input text and the target characteristic token. The method also includes generating, by a decoder, each word of a tuned summary of the input text from the learned subspace representation and from a feedback about preceding words of the tuned summary. The tuned summary is tuned to target characteristics represented by the target characteristic token.

    Content optimization for audiences
    16.
    发明授权
    Content optimization for audiences 有权

    公开(公告)号：US10922492B2

    公开(公告)日：2021-02-16

    申请号：US16024131

    申请日：2018-06-29

    Applicant: Adobe Inc.

    Inventor： Niyati Himanshu Chhaya ,  Tanya Goyal ,  Projjal Chanda ,  Kushal Chawla ,  Jaya Singh ,  Cedric Huesler

    IPC: G06F40/30

    Abstract: Techniques are disclosed to assist an author in creating content variations of a given input text to better suit the mood or the affect preferences of the target audience. Affect distribution in the content is utilized to capture these psycholinguistic preferences. According to one embodiment, in a first phase the optimal/idea psycholinguistic preference for text content aimed at a particular audience segment is determined. In a second phase, a given text content is modified to align to a target language distribution, which was determined in the first phase. In one example case, word level replacement, insertions and deletions are executed to generate a modified and coherent version of the input text. The output text thus reflects the psycholinguistic requirements of the audience.

    Machine Learning Techniques for Generating Document Summaries Targeted to Affective Tone
    18.
    发明申请
    Machine Learning Techniques for Generating Document Summaries Targeted to Affective Tone 审中-公开

    公开(公告)号：US20200257757A1

    公开(公告)日：2020-08-13

    申请号：US16270191

    申请日：2019-02-07

    Applicant: Adobe Inc.

    Inventor： Kushal Chawla ,  Balaji Vasan Srinivasan ,  Niyati Himanshu Chhaya

    IPC: G06F17/24 ,  G06F17/27 ,  G06N20/00

    Abstract: An affective summarization system provides affective text summaries directed towards affective preferences of a user, such as psychological or linguistic preferences. The affective summarization system includes a summarization neural network and an affect predictor neural network. The affect predictor neural network is trained to provide a target affect level based on a word sequence, such as a word sequence for an article or other text document. The summarization neural network is trained to provide a summary sequence based on the target affect level and on the word sequence for the text document.

    CONTENT OPTIMIZATION FOR AUDIENCES
    19.
    发明申请
    CONTENT OPTIMIZATION FOR AUDIENCES 审中-公开

    公开(公告)号：US20200004820A1

    公开(公告)日：2020-01-02

    申请号：US16024131

    申请日：2018-06-29

    Applicant: Adobe Inc.

    Inventor： Niyati Himanshu Chhaya ,  Tanya Goyal ,  Projjal Chanda ,  Kushal Chawla ,  Jaya Singh ,  Cedric Huesler

    IPC: G06F17/27

    Abstract: Techniques are disclosed to assist an author in creating content variations of a given input text to better suit the mood or the affect preferences of the target audience. Affect distribution in the content is utilized to capture these psycholinguistic preferences. According to one embodiment, in a first phase the optimal/idea psycholinguistic preference for text content aimed at a particular audience segment is determined. In a second phase, a given text content is modified to align to a target language distribution, which was determined in the first phase. In one example case, word level replacement, insertions and deletions are executed to generate a modified and coherent version of the input text. The output text thus reflects the psycholinguistic requirements of the audience.

Patent Agency Ranking